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Load packages

library(gsheet)
library(tidyverse)
Registered S3 methods overwritten by 'dbplyr':
  method         from
  print.tbl_lazy     
  print.tbl_sql      
── Attaching packages ───────────────────────────────────────────────────────────────────────────────────────────────────────────── tidyverse 1.3.1 ──
✓ ggplot2 3.3.5     ✓ purrr   0.3.4
✓ tibble  3.1.3     ✓ dplyr   1.0.7
✓ tidyr   1.1.3     ✓ stringr 1.4.0
✓ readr   2.0.1     ✓ forcats 0.5.1
── Conflicts ──────────────────────────────────────────────────────────────────────────────────────────────────────────────── tidyverse_conflicts() ──
x dplyr::filter() masks stats::filter()
x dplyr::lag()    masks stats::lag()
library(quanteda)
Package version: 3.1.0
Unicode version: 13.0
ICU version: 69.1
Parallel computing: 16 of 16 threads used.
See https://quanteda.io for tutorials and examples.
library(ggplot2)
library(plotly)
Registered S3 method overwritten by 'data.table':
  method           from
  print.data.table     
Registered S3 method overwritten by 'htmlwidgets':
  method           from         
  print.htmlwidget tools:rstudio

Attaching package: ‘plotly’

The following object is masked from ‘package:ggplot2’:

    last_plot

The following object is masked from ‘package:stats’:

    filter

The following object is masked from ‘package:graphics’:

    layout

Read data and inspect

url <- "https://docs.google.com/spreadsheets/d/1qmbPdvspf9Vg_Eab9fT34ubudF_vklJwKxf0UuJrHvw/edit?usp=sharing"

rawDF <- gsheet2tbl(url)

nameVec <- c("time", "github", "languages", "proficiency")
colnames(rawDF) <- nameVec
summary(rawDF)
     time              github           languages          proficiency  
 Length:2           Length:2           Length:2           Min.   :3.00  
 Class :character   Class :character   Class :character   1st Qu.:3.25  
 Mode  :character   Mode  :character   Mode  :character   Median :3.50  
                                                          Mean   :3.50  
                                                          3rd Qu.:3.75  
                                                          Max.   :4.00  
head(rawDF)

Count languages

languages <- as.character(rawDF$languages) %>% corpus
summary(languages)
Corpus consisting of 2 documents, showing 2 documents:

  Text Types Tokens Sentences
 text1     6      9         1
 text2     3      3         1
dfm <- tokens(languages) %>%
  dfm  %>% convert(to="data.frame") %>%
  select(!contains(",")) %>%
  summarise(across(where(is.numeric), ~ sum(.x, na.rm = TRUE))) %>%
  pivot_longer(everything(), names_to = "language", values_to = "count") 
dfm

Create plots

Simple

proficiency <- table(rawDF$proficiency)
barplot(proficiency,
   xlab="Proficiency Score", ylab="Score Count", col="red")

Styled

p1 <- ggplot(dfm) +
  aes(x=language, y=count, fill=language) +
  geom_col()
p1

Interactive

ggplotly(p1)
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